How do I evaluate segmentation results effectively?

How do I evaluate segmentation results effectively?

To evaluate segmentation results, you can use metrics like silhouette score, Davies-Bouldin index, and visual inspection.

What is the silhouette score and how is it calculated?

The silhouette score measures how similar an object is to its own cluster compared to other clusters. It's calculated using the formula: (b - a) / max(a, b), where 'a' is the average distance to points in the same cluster and 'b' is the average distance to points in the nearest cluster.

Can you explain the Davies-Bouldin index?

The Davies-Bouldin index is a metric that evaluates clustering algorithms by measuring the average similarity ratio of each cluster with the cluster that is most similar to it. Lower values indicate better clustering.

What visual methods can I use to assess segmentation results?

You can use scatter plots, heatmaps, and silhouette plots to visually assess how well your segments are defined.